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Toward ensuring safety for autonomous driving perception: Standardization progress, research advances, and perspectives
Perception systems play a crucial role in autonomous driving by reading the sensory data
and providing meaningful interpretation of the operating environment for decision-making …
and providing meaningful interpretation of the operating environment for decision-making …
[HTML][HTML] A review of deep learning-based visual multi-object tracking algorithms for autonomous driving
S Guo, S Wang, Z Yang, L Wang, H Zhang, P Guo… - Applied Sciences, 2022 - mdpi.com
Multi-target tracking, a high-level vision job in computer vision, is crucial to understanding
autonomous driving surroundings. Numerous top-notch multi-object tracking algorithms …
autonomous driving surroundings. Numerous top-notch multi-object tracking algorithms …
Bot-sort: Robust associations multi-pedestrian tracking
N Aharon, R Orfaig, BZ Bobrovsky - ar** a unique identifier for each object. In this paper, we present a new robust …
Strongsort: Make deepsort great again
Recently, Multi-Object Tracking (MOT) has attracted rising attention, and accordingly,
remarkable progresses have been achieved. However, the existing methods tend to use …
remarkable progresses have been achieved. However, the existing methods tend to use …
Motrv2: Bootstrap** end-to-end multi-object tracking by pretrained object detectors
In this paper, we propose MOTRv2, a simple yet effective pipeline to bootstrap end-to-end
multi-object tracking with a pretrained object detector. Existing end-to-end methods, eg …
multi-object tracking with a pretrained object detector. Existing end-to-end methods, eg …
Motiontrack: Learning robust short-term and long-term motions for multi-object tracking
The main challenge of Multi-Object Tracking (MOT) lies in maintaining a continuous
trajectory for each target. Existing methods often learn reliable motion patterns to match the …
trajectory for each target. Existing methods often learn reliable motion patterns to match the …
Bytetrack: Multi-object tracking by associating every detection box
Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects in
videos. Most methods obtain identities by associating detection boxes whose scores are …
videos. Most methods obtain identities by associating detection boxes whose scores are …
Deep oc-sort: Multi-pedestrian tracking by adaptive re-identification
Motion-based association for Multi-Object Tracking (MOT) has recently re-achieved
prominence with the rise of powerful object detectors. Despite this, little work has been done …
prominence with the rise of powerful object detectors. Despite this, little work has been done …
Dancetrack: Multi-object tracking in uniform appearance and diverse motion
A typical pipeline for multi-object tracking (MOT) is to use a detector for object localization,
and following re-identification (re-ID) for object association. This pipeline is partially …
and following re-identification (re-ID) for object association. This pipeline is partially …
MeMOTR: Long-term memory-augmented transformer for multi-object tracking
As a video task, Multiple Object Tracking (MOT) is expected to capture temporal information
of targets effectively. Unfortunately, most existing methods only explicitly exploit the object …
of targets effectively. Unfortunately, most existing methods only explicitly exploit the object …